From a3089e6ead32827f52b72947b367e831b7b61edf Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?=E6=BA=90=E6=96=87=E9=9B=A8?= <41315874+fumiama@users.noreply.github.com> Date: Sat, 1 Apr 2023 16:42:19 +0800 Subject: [PATCH] fix: train step2a & add arg --port --pycmd --noparallel --- .gitignore | 1 + config.py | 14 +++++- infer-web.py | 35 +++++++-------- my_utils.py | 7 +-- slicer2.py | 1 - trainset_preprocess_pipeline_print.py | 64 +++++++++++++-------------- 使用需遵守的协议-LICENSE.txt | 1 + 7 files changed, 64 insertions(+), 59 deletions(-) diff --git a/.gitignore b/.gitignore index eb7cc89..82c8a74 100644 --- a/.gitignore +++ b/.gitignore @@ -3,3 +3,4 @@ __pycache__ /TEMP *.pyd hubert_base.pt +/logs diff --git a/config.py b/config.py index f379ea7..086f882 100644 --- a/config.py +++ b/config.py @@ -1,3 +1,10 @@ +import argparse +parser = argparse.ArgumentParser() +parser.add_argument("--port", type=int, default=7865, help="Listen port") +parser.add_argument("--pycmd", type=str, default="python", help="Python command") +parser.add_argument("--colab", action='store_true', help="Launch in colab") +parser.add_argument("--noparallel", action='store_true', help="Disable parallel processing") +cmd_opts = parser.parse_args() ############离线VC参数 inp_root=r"白鹭霜华长条"#对输入目录下所有音频进行转换，别放非音频文件 opt_root=r"opt"#输出目录 @@ -7,10 +14,15 @@ person=r"weights\洛天依v3.pt"#目前只有洛天依v3 device = "cuda:0"#填写cuda:x或cpu，x指代第几张卡，只支持N卡加速 is_half=True#9-10-20-30-40系显卡无脑True，不影响质量，>=20显卡开启有加速 n_cpu=0#默认0用上所有线程，写数字限制CPU资源使用 +############python命令路径 +python_cmd=cmd_opts.pycmd +listen_port=cmd_opts.port +iscolab=cmd_opts.colab +noparallel=cmd_opts.noparallel ############下头别动 import torch if(torch.cuda.is_available()==False): - print("没有发现支持的N卡，使用CPU进行推理") + print("没有发现支持的N卡, 使用CPU进行推理") device="cpu" is_half=False if(device!="cpu"): diff --git a/infer-web.py b/infer-web.py index dd6f29f..c970f36 100644 --- a/infer-web.py +++ b/infer-web.py @@ -1,9 +1,10 @@ from multiprocessing import cpu_count import threading from time import sleep -from subprocess import Popen,PIPE,run as runn +from subprocess import Popen from time import sleep -import torch, pdb, os,traceback,sys,warnings,shutil,numpy as np,faiss +import torch, os,traceback,sys,warnings,shutil,numpy as np +import faiss #判断是否有能用来训练和加速推理的N卡 ncpu=cpu_count() ngpu=torch.cuda.device_count() @@ -33,11 +34,9 @@ from infer_pack.models import SynthesizerTrnMs256NSFsid, SynthesizerTrnMs256NSFs from scipy.io import wavfile from fairseq import checkpoint_utils import gradio as gr -import librosa import logging from vc_infer_pipeline import VC -import soundfile as sf -from config import is_half,device,is_half +from config import is_half,device,is_half,python_cmd,listen_port,iscolab,noparallel from infer_uvr5 import _audio_pre_ from my_utils import load_audio from train.process_ckpt import show_info,change_info,merge,extract_small_model @@ -222,7 +221,7 @@ def preprocess_dataset(trainset_dir,exp_dir,sr,n_p=ncpu): os.makedirs("%s/logs/%s"%(now_dir,exp_dir),exist_ok=True) f = open("%s/logs/%s/preprocess.log"%(now_dir,exp_dir), "w") f.close() - cmd="python trainset_preprocess_pipeline_print.py %s %s %s %s/logs/%s"%(trainset_dir,sr,n_p,now_dir,exp_dir) + cmd=python_cmd + " trainset_preprocess_pipeline_print.py %s %s %s %s/logs/%s "%(trainset_dir,sr,n_p,now_dir,exp_dir)+str(noparallel) print(cmd) p = Popen(cmd, shell=True)#, stdin=PIPE, stdout=PIPE,stderr=PIPE,cwd=now_dir ###煞笔gr，popen read都非得全跑完了再一次性读取，不用gr就正常读一句输出一句;只能额外弄出一个文本流定时读 @@ -242,7 +241,7 @@ def extract_f0_feature(gpus,n_p,f0method,if_f0,exp_dir): f = open("%s/logs/%s/extract_f0_feature.log"%(now_dir,exp_dir), "w") f.close() if(if_f0=="是"): - cmd="python extract_f0_print.py %s/logs/%s %s %s"%(now_dir,exp_dir,n_p,f0method) + cmd=python_cmd + " extract_f0_print.py %s/logs/%s %s %s"%(now_dir,exp_dir,n_p,f0method) print(cmd) p = Popen(cmd, shell=True,cwd=now_dir)#, stdin=PIPE, stdout=PIPE,stderr=PIPE ###煞笔gr，popen read都非得全跑完了再一次性读取，不用gr就正常读一句输出一句;只能额外弄出一个文本流定时读 @@ -266,7 +265,7 @@ def extract_f0_feature(gpus,n_p,f0method,if_f0,exp_dir): leng=len(gpus) ps=[] for idx,n_g in enumerate(gpus): - cmd="python extract_feature_print.py %s %s %s %s/logs/%s"%(leng,idx,n_g,now_dir,exp_dir) + cmd=python_cmd + " extract_feature_print.py %s %s %s %s/logs/%s"%(leng,idx,n_g,now_dir,exp_dir) print(cmd) p = Popen(cmd, shell=True, cwd=now_dir)#, shell=True, stdin=PIPE, stdout=PIPE, stderr=PIPE, cwd=now_dir ps.append(p) @@ -305,8 +304,8 @@ def click_train(exp_dir1,sr2,if_f0_3,spk_id5,save_epoch10,total_epoch11,batch_si with open("%s/filelist.txt"%exp_dir,"w")as f:f.write("\n".join(opt)) print("write filelist done") #生成config#无需生成config - # cmd = "python train_nsf_sim_cache_sid_load_pretrain.py -e mi-test -sr 40k -f0 1 -bs 4 -g 0 -te 10 -se 5 -pg pretrained/f0G40k.pth -pd pretrained/f0D40k.pth -l 1 -c 0" - cmd = "python train_nsf_sim_cache_sid_load_pretrain.py -e %s -sr %s -f0 %s -bs %s -g %s -te %s -se %s -pg %s -pd %s -l %s -c %s" % (exp_dir1,sr2,1 if if_f0_3=="是"else 0,batch_size12,gpus16,total_epoch11,save_epoch10,pretrained_G14,pretrained_D15,1 if if_save_latest13=="是"else 0,1 if if_cache_gpu17=="是"else 0) + # cmd = python_cmd + " train_nsf_sim_cache_sid_load_pretrain.py -e mi-test -sr 40k -f0 1 -bs 4 -g 0 -te 10 -se 5 -pg pretrained/f0G40k.pth -pd pretrained/f0D40k.pth -l 1 -c 0" + cmd = python_cmd + " train_nsf_sim_cache_sid_load_pretrain.py -e %s -sr %s -f0 %s -bs %s -g %s -te %s -se %s -pg %s -pd %s -l %s -c %s" % (exp_dir1,sr2,1 if if_f0_3=="是"else 0,batch_size12,gpus16,total_epoch11,save_epoch10,pretrained_G14,pretrained_D15,1 if if_save_latest13=="是"else 0,1 if if_cache_gpu17=="是"else 0) print(cmd) p = Popen(cmd, shell=True, cwd=now_dir) p.wait() @@ -351,7 +350,7 @@ def train1key(exp_dir1, sr2, if_f0_3, trainset_dir4, spk_id5, gpus6, np7, f0meth os.makedirs("%s/logs/%s"%(now_dir,exp_dir1),exist_ok=True) #########step1:处理数据 open("%s/logs/%s/preprocess.log"%(now_dir,exp_dir1), "w").close() - cmd="python trainset_preprocess_pipeline_print.py %s %s %s %s/logs/%s"%(trainset_dir4,sr_dict[sr2],ncpu,now_dir,exp_dir1) + cmd=python_cmd + " trainset_preprocess_pipeline_print.py %s %s %s %s/logs/%s "%(trainset_dir4,sr_dict[sr2],ncpu,now_dir,exp_dir1)+str(noparallel) yield get_info_str("step1:正在处理数据") yield get_info_str(cmd) p = Popen(cmd, shell=True) @@ -361,7 +360,7 @@ def train1key(exp_dir1, sr2, if_f0_3, trainset_dir4, spk_id5, gpus6, np7, f0meth open("%s/logs/%s/extract_f0_feature.log" % (now_dir, exp_dir1), "w") if(if_f0_3=="是"): yield get_info_str("step2a:正在提取音高") - cmd="python extract_f0_print.py %s/logs/%s %s %s"%(now_dir,exp_dir1,np7,f0method8) + cmd=python_cmd + " extract_f0_print.py %s/logs/%s %s %s"%(now_dir,exp_dir1,np7,f0method8) yield get_info_str(cmd) p = Popen(cmd, shell=True,cwd=now_dir) p.wait() @@ -373,7 +372,7 @@ def train1key(exp_dir1, sr2, if_f0_3, trainset_dir4, spk_id5, gpus6, np7, f0meth leng=len(gpus) ps=[] for idx,n_g in enumerate(gpus): - cmd="python extract_feature_print.py %s %s %s %s/logs/%s"%(leng,idx,n_g,now_dir,exp_dir1) + cmd=python_cmd + " extract_feature_print.py %s %s %s %s/logs/%s"%(leng,idx,n_g,now_dir,exp_dir1) yield get_info_str(cmd) p = Popen(cmd, shell=True, cwd=now_dir)#, shell=True, stdin=PIPE, stdout=PIPE, stderr=PIPE, cwd=now_dir ps.append(p) @@ -399,7 +398,7 @@ def train1key(exp_dir1, sr2, if_f0_3, trainset_dir4, spk_id5, gpus6, np7, f0meth opt.append("%s/%s.wav|%s/%s.npy|%s"%(gt_wavs_dir.replace("\\","\\\\"),name,co256_dir.replace("\\","\\\\"),name,spk_id5)) with open("%s/filelist.txt"%exp_dir,"w")as f:f.write("\n".join(opt)) yield get_info_str("write filelist done") - cmd = "python train_nsf_sim_cache_sid_load_pretrain.py -e %s -sr %s -f0 %s -bs %s -g %s -te %s -se %s -pg %s -pd %s -l %s -c %s" % (exp_dir1,sr2,1 if if_f0_3=="是"else 0,batch_size12,gpus16,total_epoch11,save_epoch10,pretrained_G14,pretrained_D15,1 if if_save_latest13=="是"else 0,1 if if_cache_gpu17=="是"else 0) + cmd = python_cmd + " train_nsf_sim_cache_sid_load_pretrain.py -e %s -sr %s -f0 %s -bs %s -g %s -te %s -se %s -pg %s -pd %s -l %s -c %s" % (exp_dir1,sr2,1 if if_f0_3=="是"else 0,batch_size12,gpus16,total_epoch11,save_epoch10,pretrained_G14,pretrained_D15,1 if if_save_latest13=="是"else 0,1 if if_cache_gpu17=="是"else 0) yield get_info_str(cmd) p = Popen(cmd, shell=True, cwd=now_dir) p.wait() @@ -630,11 +629,7 @@ with gr.Blocks() as app: with gr.TabItem("点击查看交流、问题反馈群号"): gr.Markdown(value="""xxxxx""") - import argparse - parser = argparse.ArgumentParser() - parser.add_argument("--colab", action='store_true', help="Launch in colab") - cmd_opts = parser.parse_args() - if cmd_opts.colab: + if iscolab: app.queue(concurrency_count=511, max_size=1022).launch(share=True) else: - app.queue(concurrency_count=511, max_size=1022).launch(server_name="0.0.0.0",inbrowser=True,server_port=7865,quiet=True) + app.queue(concurrency_count=511, max_size=1022).launch(server_name="0.0.0.0",inbrowser=True,server_port=listen_port,quiet=True) diff --git a/my_utils.py b/my_utils.py index 71d4b1e..c9c3343 100644 --- a/my_utils.py +++ b/my_utils.py @@ -10,10 +10,7 @@ def load_audio(file,sr): .output("-", format="s16le", acodec="pcm_s16le", ac=1, ar=sr) .run(cmd=["ffmpeg", "-nostdin"], capture_stdout=True, capture_stderr=True) ) - except ffmpeg.Error as e: - raise RuntimeError(f"Failed to load audio: {e.stderr.decode()}") from e + except Exception as e: + raise RuntimeError(f"Failed to load audio: {e}") return np.frombuffer(out, np.int16).flatten().astype(np.float32) / 32768.0 - -if __name__=='__main__' : - print(load_audio(r"C:\CloudMusic\宮野幸子,森下唯 - 月夜に謳う君 -LUNA-.mp3",16000).shape) \ No newline at end of file diff --git a/slicer2.py b/slicer2.py index 84ea78c..a09f0de 100644 --- a/slicer2.py +++ b/slicer2.py @@ -4,7 +4,6 @@ import numpy as np # This function is obtained from librosa. def get_rms( y, - *, frame_length=2048, hop_length=512, pad_mode="constant", diff --git a/trainset_preprocess_pipeline_print.py b/trainset_preprocess_pipeline_print.py index e5c9d45..a5af367 100644 --- a/trainset_preprocess_pipeline_print.py +++ b/trainset_preprocess_pipeline_print.py @@ -1,4 +1,4 @@ -import sys,os,pdb,multiprocessing +import sys,os,multiprocessing now_dir=os.getcwd() sys.path.append(now_dir) @@ -6,20 +6,15 @@ inp_root = sys.argv[1] sr = int(sys.argv[2]) n_p = int(sys.argv[3]) exp_dir = sys.argv[4] -import numpy as np,ffmpeg,os,traceback +noparallel = sys.argv[5] == "True" +import numpy as np,os,traceback from slicer2 import Slicer -from joblib import Parallel, delayed import librosa,traceback from scipy.io import wavfile import multiprocessing from my_utils import load_audio -from time import sleep -f = open("%s/preprocess.log"%exp_dir, "a+") -def printt(strr): - print(strr) - f.write("%s\n" % strr) - f.flush() +mutex = multiprocessing.Lock() class PreProcess(): def __init__(self,sr,exp_dir): @@ -40,10 +35,18 @@ class PreProcess(): self.exp_dir=exp_dir self.gt_wavs_dir="%s/0_gt_wavs"%exp_dir self.wavs16k_dir="%s/1_16k_wavs"%exp_dir + self.f = open("%s/preprocess.log"%exp_dir, "a+") os.makedirs(self.exp_dir,exist_ok=True) os.makedirs(self.gt_wavs_dir,exist_ok=True) os.makedirs(self.wavs16k_dir,exist_ok=True) + def print(self, strr): + mutex.acquire() + print(strr) + self.f.write("%s\n" % strr) + self.f.flush() + mutex.release() + def norm_write(self,tmp_audio,idx0,idx1): tmp_audio = (tmp_audio / np.abs(tmp_audio).max() * (self.max * self.alpha)) + (1 - self.alpha) * tmp_audio wavfile.write("%s/%s_%s.wav" % (self.gt_wavs_dir, idx0, idx1), self.sr, (tmp_audio*32768).astype(np.int16)) @@ -67,9 +70,9 @@ class PreProcess(): tmp_audio = audio[start:] break self.norm_write(tmp_audio, idx0, idx1) - printt("%s->Suc."%path) + self.print("%s->Suc."%path) except: - printt("%s->%s"%(path,traceback.format_exc())) + self.print("%s->%s"%(path,traceback.format_exc())) def pipeline_mp(self,infos): for path, idx0 in infos: @@ -78,27 +81,24 @@ class PreProcess(): def pipeline_mp_inp_dir(self,inp_root,n_p): try: infos = [("%s/%s" % (inp_root, name), idx) for idx, name in enumerate(sorted(list(os.listdir(inp_root))))] - ps=[] - for i in range(n_p): - p=multiprocessing.Process(target=self.pipeline_mp,args=(infos[i::n_p],)) - p.start() - ps.append(p) - for p in ps:p.join() + if noparallel: + for i in range(n_p): self.pipeline_mp(infos[i::n_p]) + else: + ps=[] + for i in range(n_p): + p=multiprocessing.Process(target=self.pipeline_mp,args=(infos[i::n_p],)) + p.start() + ps.append(p) + for p in ps:p.join() except: - printt("Fail. %s"%traceback.format_exc()) + self.print("Fail. %s"%traceback.format_exc()) + +def preprocess_trainset(inp_root, sr, n_p, exp_dir): + pp=PreProcess(sr,exp_dir) + pp.print("start preprocess") + pp.print(sys.argv) + pp.pipeline_mp_inp_dir(inp_root,n_p) + pp.print("end preprocess") if __name__=='__main__': - # f = open("logs/log_preprocess.log", "w") - printt(sys.argv) - ###################################################### - # inp_root=r"E:\语音音频+标注\米津玄师\src" - # inp_root=r"E:\codes\py39\vits_vc_gpu_train\todo-songs" - # sr=40000 - # n_p = 6 - # exp_dir=r"E:\codes\py39\dataset\mi-test" - - ###################################################### - printt("start preprocess") - pp=PreProcess(sr,exp_dir) - pp.pipeline_mp_inp_dir(inp_root,n_p) - printt("end preprocess") + preprocess_trainset(inp_root, sr, n_p, exp_dir) diff --git a/使用需遵守的协议-LICENSE.txt b/使用需遵守的协议-LICENSE.txt index 37abffc..db2094b 100644 --- a/使用需遵守的协议-LICENSE.txt +++ b/使用需遵守的协议-LICENSE.txt @@ -1,6 +1,7 @@ MIT License Copyright (c) 2023 liujing04 +Copyright (c) 2023 源文雨 本软件及其相关代码以MIT协议开源，作者不对软件具备任何控制力，使用软件者、传播软件导出的声音者自负全责。 如不认可该条款，则不能使用或引用软件包内任何代码和文件。